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A family of algorithms combining weakly predictive models into a strongly predictive model. The most common approach is called gradient boosting, and the most commonly used weak models are classification/regression trees.

A family of algorithms combining weakly predictive models (weak learners) into a strongly predictive model (super learner). The most common approach is called gradient boosting, and the most commonly used weak models are classification/regression trees. Another approach is likelihood-based boosting, and another weak learner is simple linear regression.